Information organization and visualization is essential for efficient data search, exploration and discovery, especially for large data sets. It is sometimes difficult to organize large amounts of information in a useful way. The way in which data is interpreted and converted into meaning relationships is affected by the way in which it is presented. A well designed information retrieval process can enhance comprehension, communication, hypothesis formation, and reduce search times. A useful technique to display the relationships in large data sets is through interactive visual exploration of data.
In recent years networks have been used to analyze and visualize data of many types of elements and their relationships, including social connections of friends, family and contacts, internet social groups, correlated stock prices in finance, gene interactions, genotypic and phenotypic relationships, food webs, transportation routes, sexual interactions, genealogical trees, hyperlinked documents within Wikipedia, academic papers related by common citation, academic papers related by co-authors, semantic web, actor co-occurrence within movies, metabolic pathways, disease spread, countries related by product exports, internet web pages related by links, neuronal interactions, social communications by e-mails, text messages, mobile phone calls, virus spread, human mobility, protein interactions, institutional organization, military organization, functional organization with biological cells, communication infrastructure, and product construction processes.
To facilitate the detection of larger scale patterns in a set of data, methods for information visualization have previously been developed. Many of these visualizations have been manually designed, although there are also automated visualizations which make use of software applications. Example applications include applications for organizing and searching through a document base of patent documents focus primarily on identifying similarities between patent documents but do not incorporate an interactive network visualization model.
There is a need to see detail and the larger context of data sets at the same time. In particular, there are no applications that enable a simultaneous broad view of the network and detailed understanding of a data set element or relationship in order to visualize data elements in context. Conventional applications plot information on a network, without simultaneous display of details that can be explored with respect to individual data elements. Alternatively, applications that involve information navigation on a network focus on navigation from node to node in a local context of nearby neighbors without having the ability to see a global portion of the network.